The present invention relates to error correction encoding and decoding, and more particularly, to techniques for providing greater error protection to error-prone bits generated from irregular error correction codes.
Error correcting codes are used in data recording systems to ensure data reliability and to reduce the adverse effects of channel noise. Parity codes are examples of error correction codes. Parity codes are often used to correct errors that occur in data transmitted over a communications channel or stored on a digital storage medium. For example, parity check codes are often used to correct errors in data stored on magnetic hard disks.
Error correction decoding can be performed using hard decision decoders or soft-decision decoders. Hard decision decoding is generally based on an assumption that all bits in a codeword are equally likely to be in error. Hard decision decoding generally does not consider that some bits are more reliable than others. However, hard decision decoding codes that provide un-equal protection do exist.
Soft-decision decoding receives input analog data (e.g., an equalized read-back signal or bit reliability information) and preferentially flips unreliable bits. In soft decision decoding, the log-likelihood ratio (LLR) is a measure of the likelihood of a bit being a ‘1’ divided by the likelihood of the bit being ‘0.’ A greater absolute value of LLR indicates a more reliable bit. A soft decision decoder uses the LLR for each bit to evaluate the probability that the bit is in error. Soft-decision decoding out-performs hard-decision decoding, because it is able to exploit the fact that some bits are more reliable than others.
A low density parity check (LDPC) code is a linear error-correcting code that has a parity check matrix H with a small number of nonzero elements in each row and column. LDPC codewords may be decoded using soft-decision decoding. LDPC codes can be defined over any finite field. For example, an LDPC codes can be defined over GF(2), in which “1” is the only nonzero element.
The weight (or degree) of an LDPC code refers to the number of elements that have a non-zero value among the elements constituting the parity check matrix. In a regular LDPC parity check matrix, all the rows have the same weight, and all the columns have the same weight. Thus, a regular LDPC code has the same number of non-zero elements in each column of its parity check matrix, and the same number of non-zero elements in each row of its parity check matrix. Some of the columns and/or some of the rows in a parity check matrix of an irregular LDPC code have different weights.
In a standard encoding process, a block of information bits is encoded using a generator matrix that can be derived from the parity check matrix of a LDPC code. In soft-decision decoding, the strength of error protection that is provided to each bit depends on the weight of the corresponding column in the parity check matrix that is used to decode codewords. Thus, regular LDPC codes provide the same level of error protection to each bit in the codeword, because each column in the parity check matrix has the same weight. An irregular LDPC code provides different levels of error protection to bits in the codeword, because some columns in the parity check matrix have different weights. Bits corresponding to the columns with a lower weight are provided less error protection.
Repeat-accumulate (RA) LDPC codes are another class of error correcting codes used in communications and data storage applications. RA LDPC codewords can also be decoded using soft-decision decoding. RA LDPC codes include regular RA codes, irregular RA codes, and extended irregular RA codes (eIRA codes). RA LDPC codes are weak in error protection (WEP) on the parity check bits in a codeword. RA LDPC codes provide stronger error protection to information bits than to parity check bits.
In soft-decision decoding, multiple decoding iterations are performed to cause each bit to converge to a more reliable value (i.e., a higher LLR). In each iteration of an irregular RA LDPC decoding process, the LLR for parity check bit nodes converge slower than the LLR for information bit nodes, and the LLR for parity check nodes converge to a smaller magnitude than the LLR for information bit nodes due to the irregular weight distribution.
Usually, parity check bits are thrown away after the completion of RA LDPC decoding. Only the information bits are of interest. Therefore, WEP does not cause the error rate performance of RA LDPC codes to degrade.
However, both information and parity check bits are of interest in certain applications. In these applications, the error rate performance of irregular RA LDPC codes degrades, because of the weak error protection provided to the parity check bits. Irregular RA LDPC codes provide better error protection to information bits than to parity check bits, leaving the parity check bits more vulnerable to channel noise.
The cause of this problem relates to the structure of RA LDPC codes. For example, information bits typically correspond to large column weights, and the parity check bits typically correspond to a column weight of 2. However, the last parity check bit corresponds to a single-weight column, and therefore, the last parity check bit is especially vulnerable to channel noise. The LLR of the last parity check bit is slow to converge and converges to a small magnitude. For these reasons, the last parity check bit that corresponds to a single-weight column is particularly prone to errors, and tends to cause a small number of adjacent parity check bits to have errors.
Therefore, it would be desirable to provide irregular error correcting codes that can provide greater error protection for parity check bits.